OVERVIEW

This exercise accompanies the lessons in Environmental Data Analytics on Data Exploration.

Directions

  1. Rename this file <FirstLast>_A03_DataExploration.Rmd (replacing <FirstLast> with your first and last name).
  2. Change “Student Name” on line 3 (above) with your name.
  3. Work through the steps, creating code and output that fulfill each instruction.
  4. Assign a useful name to each code chunk and include ample comments with your code.
  5. Be sure to answer the questions in this assignment document.
  6. When you have completed the assignment, Knit the text and code into a single PDF file.
  7. After Knitting, submit the completed exercise (PDF file) to the dropbox in Sakai.

TIP: If your code extends past the page when knit, tidy your code by manually inserting line breaks.

TIP: If your code fails to knit, check that no install.packages() or View() commands exist in your code.


Set up your R session

  1. Check your working directory, load necessary packages (tidyverse, lubridate), and upload two datasets: the ECOTOX neonicotinoid dataset (ECOTOX_Neonicotinoids_Insects_raw.csv) and the Niwot Ridge NEON dataset for litter and woody debris (NEON_NIWO_Litter_massdata_2018-08_raw.csv). Name these datasets “Neonics” and “Litter”, respectively. Be sure to include the subcommand to read strings in as factors.
getwd()
## [1] "/home/guest/EDE_Fall2023"
#install.packages("tidyverse")
#install.packages("lubridate")
library(tidyverse)
library(lubridate)

Neonics <- read.csv("./Data/Raw/ECOTOX_Neonicotinoids_Insects_raw.csv",stringsAsFactors = TRUE)
Neonics
Litter <- read.csv("./Data/Raw/NEON_NIWO_Litter_massdata_2018-08_raw.csv",stringsAsFactors = TRUE)
Litter

Learn about your system

  1. The neonicotinoid dataset was collected from the Environmental Protection Agency’s ECOTOX Knowledgebase, a database for ecotoxicology research. Neonicotinoids are a class of insecticides used widely in agriculture. The dataset that has been pulled includes all studies published on insects. Why might we be interested in the ecotoxicology of neonicotinoids on insects? Feel free to do a brief internet search if you feel you need more background information.

Answer:Neonictonoids are a class of pesticidies that kill insects by collapsing the nervous systems.

  1. The Niwot Ridge litter and woody debris dataset was collected from the National Ecological Observatory Network, which collectively includes 81 aquatic and terrestrial sites across 20 ecoclimatic domains. 32 of these sites sample forest litter and woody debris, and we will focus on the Niwot Ridge long-term ecological research (LTER) station in Colorado. Why might we be interested in studying litter and woody debris that falls to the ground in forests? Feel free to do a brief internet search if you feel you need more background information.

Answer:They are extremely important to mantain the health of the ecosystem. Their decomposition allows the soil to be rich.

  1. How is litter and woody debris sampled as part of the NEON network? Read the NEON_Litterfall_UserGuide.pdf document to learn more. List three pieces of salient information about the sampling methods here:

Answer: 1. 2. 3.

Obtain basic summaries of your data (Neonics)

  1. What are the dimensions of the dataset?
dim(Neonics)
## [1] 4623   30
# 4623 rows and 30 columns
  1. Using the summary function on the “Effect” column, determine the most common effects that are studied. Why might these effects specifically be of interest?
summary(Neonics$Effect)
##     Accumulation        Avoidance         Behavior     Biochemistry 
##               12              102              360               11 
##          Cell(s)      Development        Enzyme(s) Feeding behavior 
##                9              136               62              255 
##         Genetics           Growth        Histology       Hormone(s) 
##               82               38                5                1 
##    Immunological     Intoxication       Morphology        Mortality 
##               16               12               22             1493 
##       Physiology       Population     Reproduction 
##                7             1803              197

Answer: Mortality, Feeding Behaviour, Behaviour, Reproduction and Development

  1. Using the summary function, determine the six most commonly studied species in the dataset (common name). What do these species have in common, and why might they be of interest over other insects? Feel free to do a brief internet search for more information if needed.[TIP: The sort() command can sort the output of the summary command…]
summary(Neonics)
##    CAS.Number       
##  Min.   : 58842209  
##  1st Qu.:138261413  
##  Median :138261413  
##  Mean   :147651982  
##  3rd Qu.:153719234  
##  Max.   :210880925  
##                     
##                                                                                 Chemical.Name 
##  (2E)-1-[(6-Chloro-3-pyridinyl)methyl]-N-nitro-2-imidazolidinimine                     :2658  
##  3-[(2-Chloro-5-thiazolyl)methyl]tetrahydro-5-methyl-N-nitro-4H-1,3,5-oxadiazin-4-imine: 686  
##  [C(E)]-N-[(2-Chloro-5-thiazolyl)methyl]-N'-methyl-N''-nitroguanidine                  : 452  
##  (1E)-N-[(6-Chloro-3-pyridinyl)methyl]-N'-cyano-N-methylethanimidamide                 : 420  
##  N''-Methyl-N-nitro-N'-[(tetrahydro-3-furanyl)methyl]guanidine                         : 218  
##  [N(Z)]-N-[3-[(6-Chloro-3-pyridinyl)methyl]-2-thiazolidinylidene]cyanamide             : 128  
##  (Other)                                                                               :  61  
##                                                    Chemical.Grade
##  Not reported                                             :3989  
##  Technical grade, technical product, technical formulation: 422  
##  Pestanal grade                                           :  93  
##  Not coded                                                :  53  
##  Commercial grade                                         :  27  
##  Analytical grade                                         :  15  
##  (Other)                                                  :  24  
##                                                  Chemical.Analysis.Method
##  Measured                                                    : 230       
##  Not coded                                                   :  51       
##  Not reported                                                :   5       
##  Unmeasured                                                  :4321       
##  Unmeasured values (some measured values reported in article):  16       
##                                                                          
##                                                                          
##  Chemical.Purity                  Species.Scientific.Name
##  NR     :2502    Apis mellifera               : 667      
##  25     : 244    Bombus terrestris            : 183      
##  50     : 200    Apis mellifera ssp. carnica  : 152      
##  20     : 189    Bombus impatiens             : 140      
##  70     : 112    Apis mellifera ssp. ligustica: 113      
##  75     :  89    Popillia japonica            :  94      
##  (Other):1287    (Other)                      :3274      
##             Species.Common.Name
##  Honey Bee            : 667    
##  Parasitic Wasp       : 285    
##  Buff Tailed Bumblebee: 183    
##  Carniolan Honey Bee  : 152    
##  Bumble Bee           : 140    
##  Italian Honeybee     : 113    
##  (Other)              :3083    
##                                                        Species.Group 
##  Insects/Spiders                                              :3569  
##  Insects/Spiders; Standard Test Species                       :  27  
##  Insects/Spiders; Standard Test Species; U.S. Invasive Species: 667  
##  Insects/Spiders; U.S. Invasive Species                       : 360  
##                                                                      
##                                                                      
##                                                                      
##     Organism.Lifestage  Organism.Age             Organism.Age.Units
##  Not reported:2271     NR     :3851   Not reported        :3515    
##  Adult       :1222     2      : 111   Day(s)              : 327    
##  Larva       : 437     3      : 105   Instar              : 255    
##  Multiple    : 285     <24    :  81   Hour(s)             : 241    
##  Egg         : 128     4      :  81   Hours post-emergence:  99    
##  Pupa        :  69     1      :  59   Year(s)             :  64    
##  (Other)     : 211     (Other): 335   (Other)             : 122    
##                     Exposure.Type         Media.Type  
##  Environmental, unspecified:1599   No substrate:2934  
##  Food                      :1124   Not reported: 663  
##  Spray                     : 393   Natural soil: 393  
##  Topical, general          : 254   Litter      : 264  
##  Ground granular           : 249   Filter paper: 230  
##  Hand spray                : 210   Not coded   :  51  
##  (Other)                   : 794   (Other)     :  88  
##               Test.Location  Number.of.Doses        Conc.1.Type..Author.
##  Field artificial    :  96   2      :2441    Active ingredient:3161     
##  Field natural       :1663   3      : 499    Formulation      :1420     
##  Field undeterminable:   4   5      : 314    Not coded        :  42     
##  Lab                 :2860   6      : 230                               
##                              4      : 221                               
##                              NR     : 217                               
##                              (Other): 701                               
##  Conc.1..Author. Conc.1.Units..Author.              Effect    
##  0.37/  : 208    AI kg/ha  : 575       Population      :1803  
##  10/    : 127    AI mg/L   : 298       Mortality       :1493  
##  NR/    : 108    AI lb/acre: 277       Behavior        : 360  
##  NR     :  94    AI g/ha   : 241       Feeding behavior: 255  
##  1      :  82    ng/org    : 231       Reproduction    : 197  
##  1023   :  80    ppm       : 180       Development     : 136  
##  (Other):3924    (Other)   :2821       (Other)         : 379  
##               Effect.Measurement    Endpoint                   Response.Site 
##  Abundance             :1699     NOEL   :1816   Not reported          :4349  
##  Mortality             :1294     LOEL   :1664   Midgut or midgut gland:  63  
##  Survival              : 133     LC50   : 327   Not coded             :  51  
##  Progeny counts/numbers: 120     LD50   : 274   Whole organism        :  41  
##  Food consumption      : 103     NR     : 167   Hypopharyngeal gland  :  27  
##  Emergence             :  98     NR-LETH:  86   Head                  :  23  
##  (Other)               :1176     (Other): 289   (Other)               :  69  
##  Observed.Duration..Days.       Observed.Duration.Units..Days.
##  1      : 713             Day(s)               :4394          
##  2      : 383             Emergence            :  70          
##  NR     : 355             Growing season       :  48          
##  7      : 207             Day(s) post-hatch    :  20          
##  3      : 183             Day(s) post-emergence:  17          
##  0.0417 : 133             Tiller stage         :  15          
##  (Other):2649             (Other)              :  59          
##                                                                            Author    
##  Peck,D.C.                                                                    : 208  
##  Frank,S.D.                                                                   : 100  
##  El Hassani,A.K., M. Dacher, V. Gary, M. Lambin, M. Gauthier, and C. Armengaud:  96  
##  Williamson,S.M., S.J. Willis, and G.A. Wright                                :  93  
##  Laurino,D., A. Manino, A. Patetta, and M. Porporato                          :  88  
##  Scholer,J., and V. Krischik                                                  :  82  
##  (Other)                                                                      :3956  
##  Reference.Number
##  Min.   :   344  
##  1st Qu.:108459  
##  Median :165559  
##  Mean   :142189  
##  3rd Qu.:168998  
##  Max.   :180410  
##                  
##                                                                                                                                         Title     
##  Long-Term Effects of Imidacloprid on the Abundance of Surface- and Soil-Active Nontarget Fauna in Turf                                    : 200  
##  Reduced Risk Insecticides to Control Scale Insects and Protect Natural Enemies in the Production and Maintenance of Urban Landscape Plants: 100  
##  Effects of Sublethal Doses of Acetamiprid and Thiamethoxam on the Behavior of the Honeybee (Apis mellifera)                               :  96  
##  Exposure to Neonicotinoids Influences the Motor Function of Adult Worker Honeybees                                                        :  93  
##  Toxicity of Neonicotinoid Insecticides on Different Honey Bee Genotypes                                                                   :  88  
##  Chronic Exposure of Imidacloprid and Clothianidin Reduce Queen Survival, Foraging, and Nectar Storing in Colonies of Bombus impatiens     :  82  
##  (Other)                                                                                                                                   :3964  
##                                            Source     Publication.Year
##  Agric. For. Entomol.11(4): 405-419           : 200   Min.   :1982    
##  Environ. Entomol.41(2): 377-386              : 100   1st Qu.:2005    
##  Arch. Environ. Contam. Toxicol.54(4): 653-661:  96   Median :2010    
##  Ecotoxicology23:1409-1418                    :  93   Mean   :2008    
##  Bull. Insectol.66(1): 119-126                :  88   3rd Qu.:2013    
##  PLoS One9(3): 14 p.                          :  82   Max.   :2019    
##  (Other)                                      :3964                   
##  Summary.of.Additional.Parameters                                                                                                                                                                                                                       
##  Purity: \xca NR - NR | Organism Age: \xca NR - NR Not reported | Conc 1 (Author): \xca Active ingredient NR/ - NR/ AI kg/ha | Duration (Days): \xca NR - NR NR | Conc 2 (Author): \xca NR (NR - NR) NR | Conc 3 (Author): \xca NR (NR - NR) NR  : 389  
##  Purity: \xca NR - NR | Organism Age: \xca NR - NR Not reported | Conc 1 (Author): \xca Active ingredient NR - NR AI lb/acre | Duration (Days): \xca NR - NR NR | Conc 2 (Author): \xca NR (NR - NR) NR | Conc 3 (Author): \xca NR (NR - NR) NR  : 138  
##  Purity: \xca NR - NR | Organism Age: \xca NR - NR Not reported | Conc 1 (Author): \xca Active ingredient NR - NR AI kg/ha | Duration (Days): \xca NR - NR NR | Conc 2 (Author): \xca NR (NR - NR) NR | Conc 3 (Author): \xca NR (NR - NR) NR    : 136  
##  Purity: \xca NR - NR | Organism Age: \xca NR - NR Not reported | Conc 1 (Author): \xca Active ingredient NR/ - NR/ AI lb/acre | Duration (Days): \xca NR - NR NR | Conc 2 (Author): \xca NR (NR - NR) NR | Conc 3 (Author): \xca NR (NR - NR) NR: 124  
##  Purity: \xca NR - NR | Organism Age: \xca NR - NR Not reported | Conc 1 (Author): \xca Active ingredient NR - NR AI ng/org | Duration (Days): \xca NR - NR NR | Conc 2 (Author): \xca NR (NR - NR) NR | Conc 3 (Author): \xca NR (NR - NR) NR   :  94  
##  Purity: \xca NR - NR | Organism Age: \xca NR - NR Not reported | Conc 1 (Author): \xca Formulation NR - NR ml/ha | Duration (Days): \xca NR - NR NR | Conc 2 (Author): \xca NR (NR - NR) NR | Conc 3 (Author): \xca NR (NR - NR) NR             :  80  
##  (Other)                                                                                                                                                                                                                                         :3662
sort(summary(Neonics$Species.Common.Name))
##                         Ant Family                       Apple Maggot 
##                                  9                                  9 
##             Glasshouse Potato Wasp                           Lacewing 
##                                 10                                 10 
##            Southern House Mosquito            Two Spotted Lady Beetle 
##                                 10                                 10 
##           Spotless Ladybird Beetle                Braconid Parasitoid 
##                                 11                                 12 
##                       Common Thrip       Eastern Subterranean Termite 
##                                 12                                 12 
##                             Jassid                         Mite Order 
##                                 12                                 12 
##                          Pea Aphid                   Pond Wolf Spider 
##                                 12                                 12 
##              Armoured Scale Family                   Diamondback Moth 
##                                 13                                 13 
##                      Eulophid Wasp                  Monarch Butterfly 
##                                 13                                 13 
##                      Predatory Bug              Yellow Fever Mosquito 
##                                 13                                 13 
##                       Corn Earworm                  Green Peach Aphid 
##                                 14                                 14 
##                          House Fly                          Ox Beetle 
##                                 14                                 14 
##                 Red Scale Parasite                 Spined Soldier Bug 
##                                 14                                 14 
##              Western Flower Thrips Hemlock Woolly Adelgid Lady Beetle 
##                                 15                                 16 
##              Hemlock Wooly Adelgid                               Mite 
##                                 16                                 16 
##                        Onion Thrip              Araneoid Spider Order 
##                                 16                                 17 
##                          Bee Order                     Egg Parasitoid 
##                                 17                                 17 
##                       Insect Class           Moth And Butterfly Order 
##                                 17                                 17 
##       Oystershell Scale Parasitoid          Black-spotted Lady Beetle 
##                                 17                                 18 
##                       Calico Scale                Fairyfly Parasitoid 
##                                 18                                 18 
##                        Lady Beetle             Minute Parasitic Wasps 
##                                 18                                 18 
##                          Mirid Bug                   Mulberry Pyralid 
##                                 18                                 18 
##                           Silkworm                     Vedalia Beetle 
##                                 18                                 18 
##                       Codling Moth         Flatheaded Appletree Borer 
##                                 19                                 20 
##               Horned Oak Gall Wasp                 Leaf Beetle Family 
##                                 20                                 20 
##                  Potato Leafhopper         Tooth-necked Fungus Beetle 
##                                 20                                 20 
##                      Argentine Ant                             Beetle 
##                                 21                                 21 
##                          Mason Bee                           Mosquito 
##                                 22                                 22 
##                   Citrus Leafminer                    Ladybird Beetle 
##                                 23                                 23 
##                  Spider/Mite Class                Tobacco Flea Beetle 
##                                 24                                 24 
##                       Chalcid Wasp             Convergent Lady Beetle 
##                                 25                                 25 
##                      Stingless Bee               Ground Beetle Family 
##                                 25                                 27 
##                 Rove Beetle Family                      Tobacco Aphid 
##                                 27                                 27 
##                      Scarab Beetle                      Spring Tiphia 
##                                 29                                 29 
##                        Thrip Order             Ladybird Beetle Family 
##                                 29                                 30 
##                         Parasitoid                      Braconid Wasp 
##                                 30                                 33 
##                       Cotton Aphid                     Predatory Mite 
##                                 33                                 33 
##               Sweetpotato Whitefly                       Aphid Family 
##                                 37                                 38 
##                     Cabbage Looper              Buff-tailed Bumblebee 
##                                 38                                 39 
##                     True Bug Order           Sevenspotted Lady Beetle 
##                                 45                                 46 
##                       Beetle Order        Snout Beetle Family, Weevil 
##                                 47                                 47 
##                Erythrina Gall Wasp                    Parasitoid Wasp 
##                                 49                                 51 
##             Colorado Potato Beetle                      Parastic Wasp 
##                                 57                                 58 
##               Asian Citrus Psyllid                  Minute Pirate Bug 
##                                 60                                 62 
##                  European Dark Bee                           Wireworm 
##                                 66                                 69 
##                     Euonymus Scale                  Asian Lady Beetle 
##                                 75                                 76 
##                    Japanese Beetle                   Italian Honeybee 
##                                 94                                113 
##                         Bumble Bee                Carniolan Honey Bee 
##                                140                                152 
##              Buff Tailed Bumblebee                     Parasitic Wasp 
##                                183                                285 
##                          Honey Bee                            (Other) 
##                                667                                670

Answer:

  1. Concentrations are always a numeric value. What is the class of Conc.1..Author. column in the dataset, and why is it not numeric?
class(Neonics$Conc.1..Author.)
## [1] "factor"

Answer:

Explore your data graphically (Neonics)

  1. Using geom_freqpoly, generate a plot of the number of studies conducted by publication year.
ggplot(Neonics) + geom_freqpoly(aes(x=Publication.Year),bins=40)

  1. Reproduce the same graph but now add a color aesthetic so that different Test.Location are displayed as different colors.
ggplot(Neonics) + geom_freqpoly(aes(x= Publication.Year,color= Test.Location,bins=40))
## Warning in geom_freqpoly(aes(x = Publication.Year, color = Test.Location, :
## Ignoring unknown aesthetics: bins
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Interpret this graph. What are the most common test locations, and do they differ over time?

Answer:

  1. Create a bar graph of Endpoint counts. What are the two most common end points, and how are they defined? Consult the ECOTOX_CodeAppendix for more information.

[TIP: Add theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) to the end of your plot command to rotate and align the X-axis labels…]

ggplot(Neonics) + geom_histogram(aes(x=Endpoint),stat="count") + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))
## Warning in geom_histogram(aes(x = Endpoint), stat = "count"): Ignoring unknown
## parameters: `binwidth`, `bins`, and `pad`

Answer:

Explore your data (Litter)

  1. Determine the class of collectDate. Is it a date? If not, change to a date and confirm the new class of the variable. Using the unique function, determine which dates litter was sampled in August 2018.
class(Litter$collectDate)
## [1] "factor"
library(lubridate)
date_new <- ymd(Litter$collectDate)
date_new 
##   [1] "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02"
##   [6] "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02"
##  [11] "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02"
##  [16] "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02"
##  [21] "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02"
##  [26] "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02"
##  [31] "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02"
##  [36] "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02"
##  [41] "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02"
##  [46] "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02"
##  [51] "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02"
##  [56] "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02"
##  [61] "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02"
##  [66] "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02"
##  [71] "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02"
##  [76] "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02"
##  [81] "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02"
##  [86] "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02" "2018-08-02"
##  [91] "2018-08-02" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
##  [96] "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
## [101] "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
## [106] "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
## [111] "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
## [116] "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
## [121] "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
## [126] "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
## [131] "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
## [136] "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
## [141] "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
## [146] "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
## [151] "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
## [156] "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
## [161] "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
## [166] "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
## [171] "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
## [176] "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
## [181] "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30" "2018-08-30"
## [186] "2018-08-30" "2018-08-30" "2018-08-30"
class(date_new)
## [1] "Date"
  1. Using the unique function, determine how many plots were sampled at Niwot Ridge. How is the information obtained from unique different from that obtained from summary?
unique(Litter$plotID)
##  [1] NIWO_061 NIWO_064 NIWO_067 NIWO_040 NIWO_041 NIWO_063 NIWO_047 NIWO_051
##  [9] NIWO_058 NIWO_046 NIWO_062 NIWO_057
## 12 Levels: NIWO_040 NIWO_041 NIWO_046 NIWO_047 NIWO_051 NIWO_057 ... NIWO_067

Answer:

  1. Create a bar graph of functionalGroup counts. This shows you what type of litter is collected at the Niwot Ridge sites. Notice that litter types are fairly equally distributed across the Niwot Ridge sites.
ggplot(Litter) + geom_histogram(aes(x=functionalGroup),stat="count")
## Warning in geom_histogram(aes(x = functionalGroup), stat = "count"): Ignoring
## unknown parameters: `binwidth`, `bins`, and `pad`

  1. Using geom_boxplot and geom_violin, create a boxplot and a violin plot of dryMass by functionalGroup.
ggplot(Litter) + geom_boxplot(aes(x=functionalGroup,y=dryMass))

ggplot(Litter) + geom_violin(aes(x=functionalGroup,y=dryMass),draw_quantiles =c(0.25,0.5,0.75))

Why is the boxplot a more effective visualization option than the violin plot in this case?

Answer:

What type(s) of litter tend to have the highest biomass at these sites?

Answer: